In vivo CRISPR screens identify a dual function of MEN1 in regulating tumor–microenvironment interactions
Bibliographic record
Abstract
Functional genomic screens in two-dimensional cell culture models are limited in identifying therapeutic targets that influence the tumor microenvironment. By comparing targeted CRISPR–Cas9 screens in a two-dimensional culture with xenografts derived from the same cell line, we identified MEN1 as the top hit that confers differential dropout effects in vitro and in vivo. MEN1 knockout in multiple solid cancer types does not impact cell proliferation in vitro but significantly promotes or inhibits tumor growth in immunodeficient or immunocompetent mice, respectively. Mechanistically, MEN1 knockout redistributes MLL1 chromatin occupancy, increasing H3K4me3 at repetitive genomic regions, activating double-stranded RNA expression and increasing neutrophil and CD8+ T cell infiltration in immunodeficient and immunocompetent mice, respectively. Pharmacological inhibition of the menin–MLL interaction reduces tumor growth in a CD8+ T cell-dependent manner. These findings reveal tumor microenvironment-dependent oncogenic and tumor-suppressive functions of MEN1 and provide a rationale for targeting MEN1 in solid cancers. Loss of MEN1 affects tumor growth, varing with the components of the tumor microenvironment. These tumors show redistribution of MLL1 on chromatin and the activation of a viral mimicry response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".